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#1
December 11th, 2012, 09:38 AM
 DSGFD Guest
Difference between Problem Solving & Dynamic Programming

Hello sir I want to know about Difference between Problem Solving & Dynamic Programming so please give me its details.

#2
December 11th, 2012, 03:31 PM
 Super Moderator Join Date: Nov 2011
Re: Difference between Problem Solving & Dynamic Programming

Dynamic programming is a useful mathematical technique for making a sequence of interrelated decisions. It provides a systematic procedure for determining the optimal combination of decisions.

In contrast to linear programming, there does not exist a standard mathematical formulation of “the” dynamic programming problem. Rather, dynamic programming is a general type of approach to problem solving, and the particular equations used must be developed to fit each situation.

Therefore, a certain degree of ingenuity and insight into the general structure of dynamic programming problems is required to recognize when and how a problem can be solved by dynamic programming procedures. These abilities can best be developed by an exposure to a wide variety of dynamic programming applications and a study of the characteristics that are common to all these situations. A large number of illustrative examples are presented for this purpose.

For the rest of the details you can download the pdf file provided.
 DP & PS Details.pdf (740.2 KB, 52 views)
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#3
July 24th, 2020, 04:15 PM
 Unregistered Guest
Re: Difference between Problem Solving & Dynamic Programming

I am searching for Difference between Problem Solving & Dynamic Programming. Will you tell details of Dynamic programming along with list of topics to study also tell list of reference books?
#4
July 24th, 2020, 04:18 PM
 Super Moderator Join Date: Oct 2019
Re: Difference between Problem Solving & Dynamic Programming

Dynamic Programming (DP) is an algorithmic technique for solving an optimization problem by breaking it down into simpler subproblems and utilizing the fact that the optimal solution to the overall problem depends upon the optimal solution to its subproblem.

The greedy method computes its solution by making its choices in a serial forward fashion, never looking back or revising previous choices

Dynamic programming is mainly an optimization over plain recursion.

Dynamic Programming is generally slower. For example, Bellman Ford algorithm takes O(VE) time.

Dynamic programming computes its solution bottom up or top down by synthesizing them from smaller optimal sub solutions.

Please find the below attached file for the details about Dynamic programming:

Dynamic programming details

Some topics you will study:

Knapsack.
LCS.
Matrix Chain Multipication .
Coin Change.
LIS.
Edit Distance.
Balanced Partition.
Optimal Strategy for a Game.

List of some books to prepare:

Learning PHP, MySQL & JavaScript
With jQuery, CSS & HTML5
Robin Nixon

Algorithms Illuminated
Greedy Algorithms and Dynamic Programming
Tim Roughgarden

Dynamic Programming and Optimal Control, Vol. I, 4th Edition
Dimitri Bertsekas

Dynamic Programming and Optimal Control
Dimitri P. Bertsekas